基于最小二乘法的自适应拟动力子结构试验  

Adaptive Pseudo-Dynamic Substructure Testing Based on Least Square Method

作　　者：王涛[1] 吴斌[1] 张健[1] 

机构地区：[1]哈尔滨工业大学土木工程学院,黑龙江哈尔滨150090

出　　处：《结构工程师》2011年第B01期57-62,共6页Structural Engineers

基　　金：国家自然科学基金(90715036;91015004;50938001)资助项目;地震行业科研专项经费资助项目(20084190731)

摘　　要：传统拟动力子结构试验中,数值子结构采用事先假定的恢复力模型。为减弱由于数值子结构模型不准确对试验结果所带来的不利影响,本文提出了自适应拟动力子结构试验方法。在子结构试验过程中,利用观测数据在线识别试验子结构恢复力模型,同时更新与试验子结构具有相同恢复力特性的数值子结构恢复力模型参数。针对双折线恢复力滞回模型,推导出了最小二乘参数估计公式,并给出了基于最小二乘法的模型参数在线识别方法。通过数值模拟和试验验证了基于最小二乘自适应拟动力子结构试验方法的有效性。数值模拟与试验的结果均表明,基于最小二乘识别算法计算省时,具有良好的精度和鲁棒性。自适应拟动力子结构试验方法通过参数识别使得数值子结构采用了更精确的恢复力模型,从而使试验结果更加接近结构的真实响应,与一般的子结构试验方法相比具有很大的优越性。Numerical substructures adopt assumed restoring model for traditional substructure testing. To diminish the negative effort caused by the inaccuracy of the restoring model of numerical substructures, adaptive pseudo-dynamic substructure testing mehod is presented in this paper. The hysteretic model of experimental substructures is identified on line and model of the part in numerical substructures which has the same hysteretic behavior with the experimental substructure is updated on line. Estimating formulas of hysteretie parameters for bilinear hysteretic models based on least square method are derived and hysteresis on-line identification method is presented. The effectiveness of adaptive pseudo-dynamic substructure testing mehod based on least square method are verified with numerical simulations and actual tests. The results indicate that the on-line identification algorithm based least square method has good robustness and can identify hysteretic parameters rapidly and accurately. This method making numerical substructure with a more accurate hysteretie model leads to the testing process closer to the real response of the structure and has great advantage over other general substructure testing method.

关 键 词：拟动力子结构试验 自适应 恢复力模型在线识别 最小二乘法 

分 类 号：TU311.3[建筑科学—结构工程] TU317